Field Crops Research最新文献

{"title":"Optimizing application strategies of prohexadione-calcium·uniconazole composite regulator to improve lodging resistance and grain yield in rice cultivation in East China","authors":"Dengke Ma , Yimin Ding , Yifan Liu , Lin Du , You Mo , Ali Dai , Junyan Xu , Dalu Gu , Liusheng Duan , Weiming Tan","doi":"10.1016/j.fcr.2025.109931","DOIUrl":"10.1016/j.fcr.2025.109931","url":null,"abstract":"<div><h3>Context or problem</h3><div>Rice (<em>Oryza sativa</em> L.) is a major staple crop worldwide. Yet, its grain yield is frequently constrained by lodging, which disrupts the canopy structure, reduces photosynthetic efficiency, lowers grain quality, and hampers mechanical harvesting. The application of plant growth regulators (PGRs) can mitigate lodging risks; however, the individual use of uniconazole and prohexadione-calcium presents certain limitations, such as panicle development issues and high costs, respectively.</div></div><div><h3>Objective or research question</h3><div>This study aimed to determine the optimal application timing and concentration of a composite PGR, prohexadione-calcium·uniconazole (PCU), to enhance stem traits and grain yield components, thereby improving rice lodging resistance and yield.</div></div><div><h3>Methods</h3><div>A two-year field experiment was conducted to assess the effects of different PCU concentrations (90, 120, and 180 g ha⁻¹) applied at two critical growth stages: the tillering stage (I) and the jointing stage (when the first elongating internode of 50 % of plants reached 1 cm, designated as II). A water-treated control (PCU0) was included. The study evaluated plant height, stem characteristics, lodging index (LI), endogenous hormone levels, and grain yield parameters.</div></div><div><h3>Results</h3><div>Foliar application of PCU at 120 g ha⁻<sup>1</sup> during the jointing stage (PCU120-Ⅱ) significantly reduced the LI by 25.0–36.5 % and increased grain yield by 8.1–9.3 %. Compared with PCU0-Ⅱ, PCU120-Ⅱ markedly shortened the basal internode length while increasing the culm diameter and culm wall thickness. Additionally, PCU120-Ⅱ significantly reduced endogenous gibberellin A<sub>3</sub> (GA<sub>3</sub>) levels in the second internode (I-2), leading to a reduction in plant height and center of gravity height. Conversely, the elevated endogenous zeatin content promoted cell division in stem tissues, contributing to increased culm wall thickness in the basal internodes. Furthermore, PCU120-Ⅱ enhanced the accumulation of key cell wall components, including cellulose and lignin, thereby strengthening stem rigidity. According to the random forest importance ranking, culm wall thickness, lignin content, culm diameter, and cellulose content emerged as key traits for breeding lodging-resistant rice. Moreover, PCU120-Ⅱ significantly increased both the number of panicles per unit area and grain weight, which were the primary contributors to the observed yield improvement.</div></div><div><h3>Conclusions</h3><div>Applying PCU at 120 g ha<sup>−1</sup> during the jointing stage is the optimal strategy for improving rice lodging resistance and grain yield. This effect is achieved through modifications in stem morphology, hormonal balance, and grain yield components.</div></div><div><h3>Implications or significance</h3><div>This study elucidates the mechanism by which the novel composite PGR, PCU, enhances ","PeriodicalId":12143,"journal":{"name":"Field Crops Research","volume":"328 ","pages":"Article 109931"},"PeriodicalIF":5.6,"publicationDate":"2025-04-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143874993","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Nitrogen nutrition index as an in-season N diagnostic method for maize yield response to N fertilization","authors":"Leonardo Bosche ,&nbsp;Federico Gomez ,&nbsp;Francisco Palmero ,&nbsp;Aidan Kerns ,&nbsp;Trevor Hefley ,&nbsp;Curtis Ransom ,&nbsp;P.V. Vara Prasad ,&nbsp;Bradley Van De Woestyne ,&nbsp;Ignacio Ciampitti","doi":"10.1016/j.fcr.2025.109941","DOIUrl":"10.1016/j.fcr.2025.109941","url":null,"abstract":"<div><div>Assessing crop nitrogen (N) status is essential for optimizing fertilizer N inputs for maize (<em>Zea mays</em> L.<em>)</em> crop and reducing the environmental footprint of this practice. The Nitrogen Nutrition Index (NNI) offers a promising method for improved in-season N diagnosis and management. However, there is a need to identify the different types of in-season responses for the relative yield (RY) to NNI (RY-NNI) relationship to develop better management tools and identify the main drivers (weather and soil factors) governing this process. This study aimed to describe the different RY-NNI relationships and identify the main weather and soil drivers influencing these responses. We used ninety-four maize yield to fertilizer N response experiments collected using a standardized protocol from the 2014–2016 growing seasons across the United States (US) Midwestern (including eight US states). Bayesian modeling and conditional inference tree algorithm were employed to assess the different types of RY-NNI relationships and characterize key weather and soil drivers. Three distinct RY-NNI relationships were identified, 60 % of the experiments exhibited a linear-plateau response (n = 56), 27 % a linear response (n = 26), and the remaining 13 % a no response (n = 12). Pre-planting nitrate-N (NO₃-N), the Shannon Diversity Index (SDI) from late vegetative (tasseling) to end of season (maturity), and the cumulative precipitation (CPP) from V9 to tasseling were key factors influencing RY-NNI responses. Together, these top three variables accounted for ∼ 50 % of the total relative variable importance. These findings enhance the use of NNI as an in-season N diagnostic tool by providing insights into types of RY-NNI relationships and their drivers.</div></div>","PeriodicalId":12143,"journal":{"name":"Field Crops Research","volume":"328 ","pages":"Article 109941"},"PeriodicalIF":5.6,"publicationDate":"2025-04-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143875042","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Advancing agroecosystem management through strategic cover crop selection: The role of species identity and community composition for productivity and climate change mitigation","authors":"Andrea Fiorini ,&nbsp;Diego Abalos ,&nbsp;Federico Capra ,&nbsp;Giacomo Mortella ,&nbsp;Michela Lommi ,&nbsp;Nicolaj Franceschi ,&nbsp;Federico Ardenti ,&nbsp;Vincenzo Tabaglio","doi":"10.1016/j.fcr.2025.109942","DOIUrl":"10.1016/j.fcr.2025.109942","url":null,"abstract":"<div><h3>Context</h3><div>Cover cropping may improve soil fertility, nutrient cycling, and soil carbon (C) stocks, yet its effects on nitrous oxide (N₂O) emissions and soil greenhouse gas balances remain unclear. The impact of cover crop species and mixtures varies over time, requiring further study.</div></div><div><h3>Objectives</h3><div>This study aimed to assess the agronomic and environmental performance of different cover crops, including hairy vetch, rye, radish, their mixtures, and a seven-species mix, over three years.</div></div><div><h3>Methods</h3><div>Over a three-year field experiment, we tested nine cover crop treatments — including rye, hairy vetch, radish, and their mixtures — and assessed their effects on biomass production, nitrogen (N) and carbon (C) inputs, soil macronutrients (N, P, K), greenhouse gas emissions (N₂O), and yields of maize, sunflower, and soybean.</div></div><div><h3>Results</h3><div>Hairy vetch and rye produced higher biomass, while radish contributed most to soil C inputs belowground. Hairy vetch provided high N inputs (&gt;200 kg N ha⁻¹ annually) but increased N₂O emissions, revealing a trade-off between fertility and greenhouse gas emissions. Rye and radish emitted less N₂O, with rye increasing soil organic C and potassium availability. The rye and vetch mixture combined high biomass production and soil C sequestration with moderate N₂O emissions, making it a promising option for balancing productivity and sustainability. Rye-based treatments achieved a positive net soil CO₂ balance. Sunflower and maize N uptake improved after vetch and rye-vetch cover crops, while soybean yield remained unaffected.</div></div><div><h3>Conclusion and implications</h3><div>Cover crop mixtures with complementary traits can balance productivity and environmental impacts. Integrating rye and vetch enhances ecological functions, supporting sustainable crop production while mitigating climate change.</div></div>","PeriodicalId":12143,"journal":{"name":"Field Crops Research","volume":"328 ","pages":"Article 109942"},"PeriodicalIF":5.6,"publicationDate":"2025-04-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143874994","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Multi-objective optimization of agronomic practices to balance soil fertility, water productivity, and economic returns in saline-alkali farmlands","authors":"Lei Sun ,&nbsp;Jianyu He ,&nbsp;Puyuan Qi ,&nbsp;Yiming Fan ,&nbsp;Yufan Wu ,&nbsp;Jiawei Liu ,&nbsp;Quanzhong Huang ,&nbsp;Guanhua Huang","doi":"10.1016/j.fcr.2025.109928","DOIUrl":"10.1016/j.fcr.2025.109928","url":null,"abstract":"<div><h3>Context</h3><div>Optimizing agronomic management is crucial for improving soil fertility, crop growth, and resource efficiency. However, the interactions between precision irrigation, organic amendments, and straw incorporation in salinized soil remain underexplored.</div></div><div><h3>Objective</h3><div>This study aimed to evaluate the combined effects of irrigation on crop demand (IOD), organic substitution (OS), and straw return (SR) on soil fertility, crop growth, water productivity (WP), and net profit (NP) in salinized farmland, while identifying the optimal agronomic strategy through multi-objective optimization.</div></div><div><h3>Methods</h3><div>A 2022–2023 field experiment evaluated eight treatment combinations (CDI (conventional drip irrigation), SNR (straw not return), CK (chemical fertilizer only), IOD, SR, and OS) in saline-alkaline soils of arid regions. Key indicators included soil fertility, sunflower growth, salt leaching efficiency, WP, and NP. Data analysis integrated Pearson correlation, EWM-TOPSIS-AISM optimization, and partial least squares path modeling to assess variable relationships, rank treatment performance, and clarify causal pathways.</div></div><div><h3>Results</h3><div>IOD+SR+OS significantly enhanced soil fertility, increasing soil mineral nitrogen by 6.87–59.54 %, available phosphorus by 4.96–152.93 %, and exchangeable potassium by 7.02–83.07 % compared to other treatments, which in turn promoted sunflower growth, leading to improvements in plant height (9.92–63.32 %), stem diameter (7.59–47.39 %), leaf area index (19.59–176.50 %), and above-ground dry matter (7.43–68.01 %). Additionally, this integrated approach exhibited the highest salt leaching efficiency (0.0032 g kg⁻¹ mm⁻¹), effectively mitigating soil salinity. Although IOD+SR+CK achieved the highest short-term NP (22.94 and 22.74 (Thousand Chinese yuan) ha⁻¹ in 2022 and 2023), IOD+SR+OS demonstrated superior long-term sustainability by optimizing WP (1.42 kg m⁻³, increasing by up to 26.12 %). Multi-objective optimization further confirmed IOD+SR+OS as the most effective strategy for balancing soil fertility, WP, and NP in salinized farmland.</div></div><div><h3>Significance</h3><div>By highlighting the synergies among IOD, SR, and OS, this study provides empirical evidence for improving soil fertility, optimizing resource efficiency, and enhancing farm profitability in arid regions. These findings contribute to the advancement of precision agriculture strategies that foster sustainable agriculture development.</div></div>","PeriodicalId":12143,"journal":{"name":"Field Crops Research","volume":"328 ","pages":"Article 109928"},"PeriodicalIF":5.6,"publicationDate":"2025-04-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143874992","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Nitrogen reduction and split application increased grain yield and agronomic nitrogen use efficiency of oilseed flax (Linum usitatissimum. L) by increasing nitrogen status","authors":"Ming Wen ,&nbsp;Yuhong Gao ,&nbsp;Lizhuo Guo ,&nbsp;Bin Yan ,&nbsp;Peina Lu ,&nbsp;Bin Wu ,&nbsp;Yifan Wang ,&nbsp;Yue Li ,&nbsp;Zhengjun Cui ,&nbsp;Peng Xu ,&nbsp;Haidi Wang ,&nbsp;Yuanyuan Cui ,&nbsp;Xingkang Ma ,&nbsp;Yongwei Zhao ,&nbsp;Ying Li","doi":"10.1016/j.fcr.2025.109910","DOIUrl":"10.1016/j.fcr.2025.109910","url":null,"abstract":"<div><h3>Context</h3><div>Accurate monitoring of crop nitrogen status is the premise of precise nitrogen application. However, there is a lack of general diagnostic approach for the nitrogen status of oilseed flax, and the mechanism of nitrogen fertilizer managements influencing oilseed flax grain yield and agronomic nitrogen use efficiency (aNUE) is still unclear.</div></div><div><h3>Objectives or methods</h3><div>Six nitrogen application rates (0 (N0), 60 (N60), 90 (N90), 120 (N120), 150 (N150), and 180 (N180) kg hm⁻²) and three split application methods (T1, 100 % of nitrogen at pre-sowing; T2, 2/3 of nitrogen at pre-sowing + 1/3 at budding stage; T3, 1/3 of nitrogen at pre-sowing + 1/3 at branching stage + 1/3 at budding stage) were designed. A critical nitrogen concentration model for oilseed flax was constructed. Then, the effects of different nitrogen fertilizer managements on dry matter and nitrogen accumulation, distribution, translocation, grain yield, and aNUE, as well as relationships between these indices and plant accumulated N deficit (Nand)/nitrogen nutrition index (NNI) of oilseed flax were analyzed.</div></div><div><h3>Results</h3><div>The dry matter-based critical nitrogen concentration model for oilseed flax was Y= 2.4507X-0.33473, with an R2 of 0.91294. Compared with the traditional nitrogen application rate (N180), nitrogen reduction by 33 % (N120) reduced the full-season NNI, nitrogen accumulation, and TransN (pre-anthesis nitrogen translocation from vegetative organs to reproductive organs) by 8.91 %-19.77 %, 10.80 %, and 10.53 %, respectively (p &lt; 0.05), and increased Nand, dry matter accumulation, proportions of dry matter allocated to leaves (PDL) and reproductive organs (PDR) at maturity stage, TransD (pre-anthesis dry matter translocation from vegetative organs to reproductive organs), TransD rate, grain yield, and aNUE by 73.42 %-118.31 %, 4.24 %, 4.81 %, 3.02 %, 9.73 %, 15.89 %, 7.43 %, and 121.92 %, respectively (p &lt; 0.05). Compared with T1, T2 increased the dry matter accumulation, PDL, PDR, TransD, nitrogen accumulation, proportion of nitrogen allocated to reproductive organs at maturity stage, grain yield, and aNUE by 4.99 %, 45.42 %, 4.00 %, 21.80 %, 11.24 %, 8.87 %, 4.09 %, and 50.95 %, respectively (p &lt; 0.05).</div></div><div><h3>Conclusions or implications</h3><div>Among the nitrogen fertilizer managements, the optimal mode N120T2 could improve oilseed flax nitrogen status, coordinate the source-sink relationship in plants to efficiently use photosynthetic assimilates, and promote the translocation of photosynthetic assimilates to sink organs in the late growth stage, thereby increasing the grain yield and aNUE. This study will provide a technical means for precise nitrogen fertilization and yield increase in oilseed flax in the semi-arid region in China.</div></div>","PeriodicalId":12143,"journal":{"name":"Field Crops Research","volume":"328 ","pages":"Article 109910"},"PeriodicalIF":5.6,"publicationDate":"2025-04-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143864995","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Intercropping lablab with maize increases grain production and soil cover, and reduces pest pressure in Tanzania","authors":"Sasha Loewen ,&nbsp;Neil Miller ,&nbsp;Michelle Carkner ,&nbsp;Wilfred Mariki ,&nbsp;Martin Entz","doi":"10.1016/j.fcr.2025.109916","DOIUrl":"10.1016/j.fcr.2025.109916","url":null,"abstract":"<div><h3>Background</h3><div>East African farmers and researchers are sharing a renewed interest in <em>Lablab purpureus</em> (L.) Sweet, a multipurpose leguminous cover crop. Lablab can produce food and fodder, fix nitrogen, scavenge resources, protect the soil, and tolerate drought. To capitalize on its potential, lablab requires more research into its basic agronomy, particularly under intercropping situations in which it is usually grown by small-holder farmers in East Africa.</div></div><div><h3>Objectives</h3><div>The study aimed to understand the effects of lablab-maize intercropping through three measured ecosystem services: 1) grain production of lablab and maize, assessed in yield and land equivalent ratio; 2) late season soil cover of living plant material; and 3) major lablab insect pests: pod boring caterpillars (<em>Maruca vitrata, Helicoverpa armigera, Etiella zinckenella</em>) and pod sucking coreid bugs (<em>Riptortus pedestris, Clavigralla tomentosicollis</em>).</div></div><div><h3>Methods</h3><div>In this study, lablab was intercropped with maize across two agro-ecozones in northern Tanzania over three years. Yield data was collected from both crop species, while late season soil cover and insect pressure focused on lablab. A simple economic analysis examined net return of sole and intercropping as a response to the costs of seed and harvesting.</div></div><div><h3>Results</h3><div>Over the six environments, intercropping reduced lablab grain yields by 35 % (p = 0.009); intercropping reduced maize yields marginally though this was not found to be significant (p = 0.087). The land equivalent ratio of maize and lablab, ranged from 1.36 to 1.96 across environments. Under adequate moisture conditions lablab grown with maize produced 58 % more late season ground cover than when lablab was sole cropped (p = 0.039), whereas in the driest environments, the opposite trend was observed (p = 0.011). The number of pod boring caterpillars (p = 0.052) and pod sucking coreid bugs (p &lt; 0.001) were reduced by 34 % and 57 % respectively by intercropping. Intercropping produced a higher net return than sole cropping lablab or maize.</div></div><div><h3>Conclusions</h3><div>These results demonstrate the diverse benefits of growing maize with lablab allowing for greater food production, increased soil protection, and reduced pest pressure. Of particular importance was the negligible effect of lablab grown with maize, on maize grain yield, highlighting that the detractions of intercropping in smallholder agriculture are outweighed by the advantages. Continued lablab research to identify best agronomic practices and new cultivars will encourage its adoption and help East African farmers diversify and strengthen their cropping systems.</div></div>","PeriodicalId":12143,"journal":{"name":"Field Crops Research","volume":"328 ","pages":"Article 109916"},"PeriodicalIF":5.6,"publicationDate":"2025-04-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143860338","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Knowledge-guided machine learning with multivariate sparse data for crop growth modelling","authors":"Jingye Han ,&nbsp;Liangsheng Shi ,&nbsp;Qi Yang ,&nbsp;Jin Yu ,&nbsp;Ioannis N. Athanasiadis","doi":"10.1016/j.fcr.2025.109912","DOIUrl":"10.1016/j.fcr.2025.109912","url":null,"abstract":"<div><h3>Context</h3><div>Process-based crop models are widely used to simulate the crop growth process. However, these models face limitations due to the simplified process representation and challenges in parameter estimation. Machine learning methods, as an emerging paradigm, have shown potential in circumventing these limitations, but they are criticized for their black-box nature that does not necessarily encompass known crop growth mechanisms, and their demand for big data that may be not available in most agricultural applications.</div></div><div><h3>Objective</h3><div>This research aims to propose a deep learning architecture that can leverage agronomic knowledge and sparse observational data for crop multivariable simulation, thereby establishing a novel paradigm for crop growth modeling.</div></div><div><h3>Methods</h3><div>We propose a Deep learning Crop Growth Model (DeepCGM) with a mass-conserving architecture that adheres to the principles of crop growth. Two additional knowledge-guided constraints regarding crop physiology and model convergence are designed to train the model with sparse datasets. An observational dataset from a two-year rice experiment of 105 plots is used to evaluate the DeepCGM against a process-based crop model (ORYZA2000) and two classical deep learning models, also employing augmentation methods. To demonstrate the validity and generalizability of the proposed model, we also conducted a replication case study of a three-year rice experiment totaling 122 plots.</div></div><div><h3>Results</h3><div>The DeepCGM architecture produces physically plausible crop growth curves for all simulated variables, while the classical machine learning models may make unreasonable predictions that violate the law of mass conservation. Furthermore, DeepCGM simulates more accurately the observed growth process when compared with the traditional process-based model, with overall accuracy (weighted normalized mean square error) across all variables improves by 8.3 % (2019) and 16.9 % (2018).</div></div><div><h3>Conclusions</h3><div>Knowledge-guided deep learning can integrate the principal mechanisms of crop growth process with deep learning. It addresses the issue of data scarcity, and thereby facilitating data-driven crop growth modelling with multivariable sparse datasets.</div></div><div><h3>Implications</h3><div>OR SIGNIFICANCE: This study highlights the potential of knowledge-guided deep learning to overcome structural error due to the simplification in conventional crop models and reduce the data requirements of data-driven models. The capacity to autonomously identify multivariable dynamic patterns in crop growth from sparse data suggests a new generation of crop growth models.</div></div>","PeriodicalId":12143,"journal":{"name":"Field Crops Research","volume":"328 ","pages":"Article 109912"},"PeriodicalIF":5.6,"publicationDate":"2025-04-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143860322","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Soybean genetic progress of maturity group IV cultivars under well-watered and drought stress conditions in central Argentina between 1984 and 2014","authors":"Matías de Felipe ,&nbsp;Gabriel Santachiara ,&nbsp;Lucas Borrás ,&nbsp;José L. Rotundo","doi":"10.1016/j.fcr.2025.109903","DOIUrl":"10.1016/j.fcr.2025.109903","url":null,"abstract":"<div><h3>Context</h3><div>Soybean genetic gain in central Argentina has traditionally been estimated under high-yielding conditions. To the present, the contribution of breeding efforts over a water gradient is not known.</div></div><div><h3>Objective</h3><div>To evaluate soybean yield genetic gain under contrasting water availability scenarios to (i) investigate breeding contributions to soybean yield potential and drought stress tolerance, and (ii) evaluate the physiological mechanisms behind the observed yield increases.</div></div><div><h3>Methods</h3><div>We used six cultivars belonging to maturity group IV, which were released into the market between 1984 and 2014. These cultivars were evaluated under well-watered and drought-stressed conditions. Nitrogen (N) capture, partitioning, and concentration were evaluated to understand the physiological attributes that explain seed yield changes over time.</div></div><div><h3>Results</h3><div>On average, the water-stressed condition yielded 61 % less compared to the well-watered. Absolute yield genetic progress was higher in the well-watered environment (31.6 and 12.8 kg ha⁻¹ year⁻¹ for the well-watered and stressed conditions, respectively), but relative yield gain was similar (1 % year⁻¹). Absolute yield changes over time were correlated to higher total N capture (2.1 and 0.5 kg N ha⁻¹ year⁻¹ for the well-watered and stressed condition, respectively). Biological N fixation from emergence to maturity was identified as the driver of this differential N uptake (1.4 and 0.5 kg N ha⁻¹ year⁻¹ in the well-watered and water stressed environment, respectively). More than proportional increases in absolute biological N fixation genetic progress during vegetative stages explained the higher biological N fixation in newer genotypes grown under well-watered conditions (0.5 and 0.03 kg N ha⁻¹ year⁻¹, for the well-watered and stressed condition, respectively).</div></div><div><h3>Conclusions</h3><div>Within the limited set of tested varieties, breeding efforts delivered higher yield potential with some degree of drought stress tolerance. Biological N-fixation modifications are responsible for the absolute yield genetic gain differences in well-watered vs. drought environments. Higher BNF in vegetative stages explained the higher yield potential of the latest cultivars released to the market in this study.</div></div><div><h3>Implications</h3><div>This study complements genetic gain estimations in central Argentina by evaluating the yield trajectories under contrasting water scenarios. Future investigations should focus on the genetic determinants of the processes related to total N uptake and the biological N fixation.</div></div>","PeriodicalId":12143,"journal":{"name":"Field Crops Research","volume":"328 ","pages":"Article 109903"},"PeriodicalIF":5.6,"publicationDate":"2025-04-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143860320","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Relevance of grain number and grain weight on barley yield responses to environmental and genetic factors","authors":"Román A. Serrago ,&nbsp;Guillermo A. García ,&nbsp;Roxana Savin ,&nbsp;Daniel J. Miralles ,&nbsp;Gustavo A. Slafer","doi":"10.1016/j.fcr.2025.109922","DOIUrl":"10.1016/j.fcr.2025.109922","url":null,"abstract":"<div><h3>Context</h3><div>Global food demand is projected to rise, making it essential to enhance agricultural production to ensure food security while minimizing environmental impacts, particularly in the face of climate change challenges. Understanding the determination of grain yield (GY) in barley is crucial for future advancements in this crop.</div></div><div><h3>Objective</h3><div>This study examines the relationships between the two major components of GY (grain number-GN and grain weight-GW), when driven by genetic and environmental factors.</div></div><div><h3>Methods</h3><div>We compiled data of GY and its numerical components (i.e. GN and GW) to generate a large and unbiased database from every single paper having the word “barley” in the title published over 25 years in four prestigious international journals: Field Crop Research, European Journal of Agronomy, Crop Science and Crop and Pasture Science (formerly Australian Journal of Agricultural Research) between January 1996 and December 2021, both inclusive.</div></div><div><h3>Results</h3><div>GN was significantly better correlated with GY than GW, accounting for 86 % of the variation in GY compared to just 13 % for GW. The changes in GY responsiveness to environmental and genetic factors were mainly due to variations in GN, especially in scenarios with high responsiveness. In contrast, low-responsiveness cases showed trade-offs between GN and GW, suggesting compensatory mechanisms that may not accurately reflect competition for resources.</div></div><div><h3>Conclusions</h3><div>The potential to increase barley GY relies heavily on GN, emphasizing the need to optimise conditions during the critical period of GN determination.</div></div><div><h3>Implications</h3><div>Barley crops under typical field conditions are generally not limited by resource availability during grain filling.</div></div>","PeriodicalId":12143,"journal":{"name":"Field Crops Research","volume":"328 ","pages":"Article 109922"},"PeriodicalIF":5.6,"publicationDate":"2025-04-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143860319","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Efficient fertilization pattern for rice production within the rice-wheat systems","authors":"Shen Gao,&nbsp;Haoyu Qian,&nbsp;Weiwei Li,&nbsp;Yuhui Wang,&nbsp;Jianwei Zhang,&nbsp;Weike Tao,&nbsp;Jie Sun,&nbsp;Yanfeng Ding,&nbsp;Zhenghui Liu,&nbsp;Yu Jiang,&nbsp;Ganghua Li","doi":"10.1016/j.fcr.2025.109925","DOIUrl":"10.1016/j.fcr.2025.109925","url":null,"abstract":"<div><h3>Context</h3><div>Rice is a staple food for nearly half of the global population. Traditional nitrogen (N) fertilization practices, characterized by high inputs and frequent applications, face increasing challenges related to low N use efficiency (NUE) and rising labor costs.</div></div><div><h3>Research question</h3><div>Previous studies have highlighted the benefits of controlled-release blended fertilizers (CRBF) for enhancing rice production. While limited research has been conducted on the effects of CRBF with different fertilization techniques and their applicability within rice-wheat systems.</div></div><div><h3>Methods</h3><div>A three-year field experiment was conducted at two sites with contrasting soil fertility levels. Six treatments were evaluated: broadcast conventional fertilization of urea (BCF), broadcast conventional fertilization of urea with a 25 % reduction in N (BRF), broadcast fertilization of CRBF with a 25 % reduction in N (BBF), whole-layer fertilization of CRBF with a 25 % reduction in N (WBF), side-deep fertilization of CRBF with a 25 % reduction in N (SBF), and a control without N fertilization.</div></div><div><h3>Results</h3><div>Compared to BCF, SBF increased rice yield by 3.2–8.8 % primarily due to a 5.1–6.7 % increase in panicle numbers, and all CRBF treatments enhanced NUE by 27.6–60.8 % with SBF exhibiting the highest. Notably, SBF improved rice yield and NUE by 6.0–7.0 % and 19.4–25.2 % compared to other CRBF treatments in low-fertility site, respectively, while no significant differences were observed among CRBF treatments in high-fertility site. This pattern reflects the differing responses of rice growth and soil N availability to fertilization patterns under varying soil fertility conditions. Our structural equation model results indicate that fertilization patterns primarily influence rice yield by affecting soil NH₄⁺-N levels and subsequently altering root growth. Economic analysis revealed that SBF resulted in a 37.2–40.1 % increase in net income compared to BCF, primarily due to reduced labor costs and improved yields, with smaller differences among CRBF treatments in high-fertility site.</div></div><div><h3>Conclusions</h3><div>CRBF emerges as a viable alternative to conventional N fertilization, effectively delivering high rice yields and enhanced economic returns across sites with varying soil fertility. SBF optimizes N supply and boosts rice production, yielding significant increases in both yield and NUE, particularly in low-fertility environments.</div></div><div><h3>Implications</h3><div>The findings of this study offer a novel perspective on achieving high yields and efficient fertilization strategies in rice cultivation within rice-wheat systems, potentially guiding future agricultural practices toward improved sustainability and productivity.</div></div>","PeriodicalId":12143,"journal":{"name":"Field Crops Research","volume":"328 ","pages":"Article 109925"},"PeriodicalIF":5.6,"publicationDate":"2025-04-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143855096","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}